"Please add the following callbacks" warning

🐛 Bug

Pytorch Lightning emits a false positive (?) warning when restoring from checkpoint during model tuning with auto_lr_find.

To Reproduce

import os

import torch
from torch.utils.data import DataLoader, Dataset

from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.callbacks import ModelCheckpoint


class RandomDataset(Dataset):
    def __init__(self, size, length):
        self.len = length
        self.data = torch.randn(length, size)

    def __getitem__(self, index):
        return self.data[index]

    def __len__(self):
        return self.len


class BoringModel(LightningModule):
    def __init__(self, lr=0.1):
        self.save_hyperparameters()
        super().__init__()
        self.layer = torch.nn.Linear(32, 2)

    def forward(self, x):
        return self.layer(x)

    def training_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("train_loss", loss)
        return {"loss": loss}

    def validation_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("valid_loss", loss)

    def test_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("test_loss", loss)

    def configure_optimizers(self):
        return torch.optim.SGD(self.layer.parameters(), lr=self.hparams.lr)

    def train_dataloader(self):
        return DataLoader(RandomDataset(32, 1024), batch_size=2, num_workers=8)

    def val_dataloader(self):
        return DataLoader(RandomDataset(32, 1024), batch_size=2, num_workers=8)

    def test_dataloader(self):
        return DataLoader(RandomDataset(32, 1024), batch_size=2, num_workers=8)



def run():
    model = BoringModel()

    trainer = Trainer(
        default_root_dir=os.getcwd(),
        max_epochs=1,
        auto_lr_find=True,
        callbacks=[ModelCheckpoint()]
    )
    trainer.tune(model, lr_find_kwargs={"early_stop_threshold": None})


if __name__ == "__main__":
    run()

Expected behavior

No warnings

Actual behavior

/usr/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py:1721: UserWarning: Be aware that when using `ckpt_path`, callbacks used to create the checkpoint need to be provided during `Trainer` instantiation. Please add the following callbacks: ["ModelCheckpoint{'monitor': None, 'mode': 'min', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}"].

Environment

* CUDA:
	- GPU:
		- NVIDIA GeForce GTX 1050
	- available:         True
	- version:           11.3
* Packages:
	- numpy:             1.22.3
	- pyTorch_debug:     False
	- pyTorch_version:   1.11.0+cu113
	- pytorch-lightning: 1.6.0
	- tqdm:              4.63.2
* System:
	- OS:                Linux
	- architecture:
		- 64bit
		- ELF
	- processor:         
	- python:            3.10.4
	- version:           #1 SMP PREEMPT Mon Mar 28 09:16:36 UTC 2022

cc @otaj @akihironitta @borda @rohitgr7

[RuRo]

I don’t really know, why is this happening or how should this be fixed, to be honest. Also, I am really busy right now, so even if I was familiar with the internals of the checkpointing mechanism, I still wouldn’t be able to contribute to this issue right now.

[RuRo]

@rohitgr7 Sorry, I don’t understand the question. The example code, that I provided, is a full example. I am not passing any checkpoint paths anywhere.

I think, that the checkpoint is created and restored automatically by auto_lr_find during tune.